1. Field of the Disclosure
The present application relates to image sensors and associated electronic circuits suitable for sensing radiation at visible, UV, deep UV (DUV), vacuum UV (VUV), and extreme UV (EUV) wavelengths, and to methods for operating such image sensors. The sensors and circuits are particularly suitable for use in inspection systems, including those used to inspect photomasks, reticles, and semiconductor wafers.
2. Related Art
The integrated circuit industry requires inspection tools with increasingly higher sensitivity to detect ever smaller defects and particles whose sizes may be smaller than 20 nm. Those same inspection tools need to be capable of detecting large defects such as scratches and water marks, which may have dimensions ranging from less than 1 μm to multiple mm, and of measuring the surface roughness or haze which may have peak-to-valley amplitudes of a few nm or less than 1 nm. The inspection tools must also be able to detect defects and particles on, or within, high-reflectivity and low-reflectivity patterns and films.
Small particles, small defects, low contrast defects, and low-amplitude roughness scatter light only very weakly. To detect small defects or particles on photomasks, reticles, and semiconductor wafers, low-noise sensors with low-noise driving and readout electronics are required. The noise level of the signal depends on the intrinsic noise level of the sensor, on the noise level of the readout electronics, and on the amount of noise that is coupled into the signals from internal and external sources, including the clock signals driving the sensor and associated electronics.
U.S. Pat. No. 7,609,309, entitled “Continuous clocking of TDI sensors”, issued on Oct. 27, 2009 and U.S. Pat. No. 7,952,633, entitled “Apparatus for continuous clocking of TDI sensors”, issued on May 31, 2011 describe waveforms that are useful for driving the clocks of low-noise CCD sensors. The '633 patent further describes a circuit using an FPGA, digital-to-analog converters (DACs), filters, and power drivers or buffers for generating those waveforms and driving a CCD sensor. Multiple integrated circuits are required to implement such a circuit. For CCD sensors with one million or more pixels and tens or hundreds of output channels, many integrated circuits and a large circuit board area would be needed to implement such a circuit. This implementation would result in some of the signals having to travel long (e.g. multi-cm) distances to the sensor, thereby making it difficult to control noise, cross talk, and ground return currents well enough to enable low-level signal detection from the sensor.
An important limitation of prior art CCD sensors and driving circuits can be appreciated by referring to FIG. 11, which illustrates the timing of a signal readout from a CCD. FIG. 11 shows the waveform of output voltage 1110 and the waveform of reset clock 1101, both as a function of time. The reset clock resets the output voltage after one pixel so that the next pixel can be output. When the reset clock 1101 is high (positive) as indicated by arrow 1102, the output charge from the prior pixel is discharged so that the output signal settles down to a reset level indicated by the waveform at arrow 1115.
Output voltage 1110 illustrates several practical issues that can degrade the signal-to-noise ratio and accuracy of the output signal of CCD image sensors, particularly when the sensor is operated at high speed as is required for inspection and metrology applications in semiconductor and related industries. When the reset clock 1101 switches from a low voltage to a high voltage as shown by the waveform at arrow 1103, some of that voltage swing is coupled to the output voltage because the reset transistor is necessarily physically located on the CCD adjacent to the output sensing node. This coupling destabilizes the output voltage 1110 as indicated by the waveform at arrow 1112.
Furthermore, when the reset clock 1101 goes low as indicated by the waveform at arrow 1104, that high-to-low transition is similarly coupled to the output voltage and destabilizes it as indicated by the waveform at arrow 1114. After a little time, the output voltage 1110 settles down and stabilizes at the reset level indicated by the waveform at 1115. When the signal from a pixel is transferred to the output, the output voltage decreases from the reset level to a lower level, such as the level indicated by arrow 1117 because the signal comprises electrons and is, hence, a negative charge. In FIG. 11, the level indicated by arrow 1117 represents the output voltage corresponding to a saturated pixel, i.e. a maximum signal, and another level indicated by arrow 1119 represents the output voltage corresponding to a signal that is significantly less than the maximum. Although not shown, typically there will be some settling time after the transition from the reset level of the waveform indicated by arrow 1115 to the signal levels of the waveform indicated by arrows 1117 or 1119.
In FIG. 11, the signal in the first pixel is proportional to the difference between the output voltages at arrows 1117 and 1115, and the signal in the second pixel is proportional to the difference between the output voltages at arrows 1115 and 1119. Usually correlated double sampling is used to measure the difference between the reset voltage at arrow 1115 and the output voltage such as at arrows 1117 and 1119. Correlated double sampling is a well-known technique and is described, for example, by J. R. Janesick, “Scientific Charge-Coupled Devices”, SPIE Press, 2001, pp. 556-561.
As can be appreciated from FIG. 11, when the signal needs to be read out at high speed, such as a speed of about 25 MHz or more, there is only a short time for the output voltage 1110 to settle to the reset voltage at arrow 1115 and the signal voltage, such as at arrows 1117 and 1119. For example at 50 MHz, the total time for one pixel is 20 ns. The reset clock pulses must necessarily be much shorter than this time with rise and fall times of, at most, 1-2 ns. Such short pulses with fast rise and fall times necessarily cause significant destabilization of the output voltage. Only a few ns are available for the output voltage to settle. In some cases, the signal may not have enough time to fully stabilize leading to noisy image data.
Therefore, a need arises for an image sensor and associated electronics capable of acquiring image data at high speed with low noise yet overcoming some, or all, of the above disadvantages.